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Abstract:

An unevenness inspection apparatus including: an image pickup section
obtaining a pickup image of a test object; an image generating section
generating each of a color unevenness inspection image and a luminance
unevenness inspection image based on the pickup image; a calculating
section calculating an evaluation parameter using both of the color
unevenness inspection image and the luminance unevenness inspection
image; and an inspecting section performing unevenness inspection using
the calculated evaluation parameter. The calculating section calculates
the evaluation parameter in consideration of unevenness visibility for
both color and luminance.

Claims:

1. An unevenness inspection apparatus comprising: an image pickup section
obtaining a pickup image of a test object; an image generating section
generating each of a color unevenness inspection image and a luminance
unevenness inspection image based on the pickup image; a calculating
section calculating an evaluation parameter using both of the color
unevenness inspection image and the luminance unevenness inspection
image; and an inspecting section performing unevenness inspection using
the calculated evaluation parameter, wherein the calculating section
calculates the evaluation parameter in consideration of unevenness
visibility for both color and luminance.

2. The unevenness inspection apparatus according to claim 1, wherein the
calculating section calculates a color unevenness evaluation parameter
using the color unevenness inspection image and calculates a luminance
unevenness evaluation parameter using the luminance unevenness inspection
image; and the calculating section calculates a total evaluation
parameter as the evaluation parameter by performing weighting addition of
the color unevenness evaluation parameter and the luminance unevenness
evaluation parameter.

3. The unevenness inspection apparatus according to claim 2, wherein,
when the color unevenness evaluation parameter is Ec, the luminance
unevenness evaluation parameter is El, and weighting coefficients are A
and B, the total evaluation parameter E is given by Expression (1) given
below, and each of the weighting coefficients A and B is determined in
consideration of the unevenness visibility. E=A×Ec+B×El (1)

4. The unevenness inspection apparatus according to claim 2, wherein the
inspecting section determines that a degree of unevenness in the test
object is greater as the total evaluation parameter increases, and the
inspecting section determines that the degree of unevenness in the test
object is smaller as the total evaluation parameter decreases.

5. The unevenness inspection apparatus according to claim 1, wherein the
image generating section generates the color unevenness inspection image
while performing correction processing in consideration of a difference
in color unevenness visibility depending on colors.

6. The unevenness inspection apparatus according to claim 5, wherein the
image generating section calculates chroma while performing the
correction processing in each unit region of the pickup image, and uses
the calculated chroma to generate the color unevenness inspection image.

8. The unevenness inspection apparatus according to claim 2, wherein a
chroma edge area ratio and a color unevenness area ratio are used as the
color unevenness evaluation parameter, the chroma edge area ratio being
an area ratio of a chroma edge region to a whole region of the test
object, the color unevenness area ratio being an area ratio of a color
unevenness region to the whole region of the test object.

9. The unevenness inspection apparatus according to claim 8, wherein the
chroma edge area ratio, the color unevenness area ratio, and maximum
chroma in the whole color unevenness region are used as the color
unevenness evaluation parameter.

10. The unevenness inspection apparatus according to claim 9, wherein the
calculating section calculates each of the chroma edge area ratio, the
color unevenness area ratio, and the maximum chroma using the color
unevenness inspection image, and the calculating section calculates the
color unevenness evaluation parameter by performing weighting addition of
the chroma edge area ratio, the color unevenness area ratio, and the
maximum chroma.

11. The unevenness inspection apparatus according to claim 8, wherein the
chroma edge region is a region in which amount of change in chroma per
unit length in the test object or unit viewing angle is equal to or
larger than a predetermined threshold value.

12. The unevenness inspection apparatus according to claim 2, wherein a
luminance edge area ratio and a luminance unevenness area ratio are used
as the luminance unevenness evaluation parameter, the luminance edge area
ratio being an area ratio of a luminance edge region to a whole region of
the test object, the luminance unevenness area ratio being an area ratio
of a luminance unevenness region to the whole region of the test object.

13. The unevenness inspection apparatus according to claim 12, wherein
the luminance edge area ratio, the luminance unevenness area ratio, and a
maximum luminance difference are used as the luminance unevenness
evaluation parameter, the maximum luminance difference being a difference
value between maximum luminance in the whole luminance unevenness region
and an average luminance in a white-color image.

14. The unevenness inspection apparatus according to claim 13, wherein
the calculating section calculates each of the luminance edge area ratio,
the luminance unevenness area ratio, and the maximum luminance difference
using the luminance unevenness inspection image, and the calculating
section calculates the luminance unevenness evaluation parameter by
performing weighting addition of the luminance edge area ratio, the
luminance unevenness area ratio, and the maximum luminance difference.

15. The unevenness inspection apparatus according to claim 12, wherein
the luminance edge region is a region in which amount of change in
luminance per unit length in the test object or unit viewing angle is
equal to or larger than a predetermined threshold value.

16. The unevenness inspection apparatus according to claim 1, wherein the
test object is a display screen of a display unit performing color image
display.

17. An unevenness inspection method comprising: obtaining a pickup image
of a test object; generating each of a color unevenness inspection image
and a luminance unevenness inspection image based on the pickup image;
calculating an evaluation parameter using both of the color unevenness
inspection image and the luminance unevenness inspection image; and
performing unevenness inspection using the calculated evaluation
parameter, wherein the calculating the evaluation parameter is performed
in consideration of unevenness visibility for both color and luminance.

Description:

CROSS REFERENCES TO RELATED APPLICATIONS

[0001] The present application claims priority to Japanese Priority Patent
Applications JP 2011-136930 filed in the Japan Patent Office on Jun. 21,
2011, and JP JP 2012-101419 filed in the Japan Patent Office on Apr. 26,
2012, the entire contents of which are hereby incorporated by reference.

BACKGROUND

[0002] The present disclosure is related to an unevenness inspection
apparatus and an unevenness inspection method for carrying out an
unevenness inspection (color unevenness inspection and luminance
unevenness inspection) in color images and the like.

[0003] In the past, a color unevenness or a luminance unevenness
inspection in mass production lines of display units using CRTs (Cathode
Ray Tubes), LCDs (Liquid Crystal Displays), and the like that are allowed
to display color images has been mainly performed utilizing a sensory
test based on a comparison with a limit sample. This technique, which is
achieved in such a manner that a display screen on a display unit
targeted for inspection is directly viewed by a human, provides an
inspection similar to actual status of use, and a simple testing method.

[0004] However, such a technique depends mostly on the ability of an
individual inspecting staff, and thus the inspection quality is
influenced by a individual difference among inspecting staffs or a
fatigue level of an inspecting staff, which makes it difficult to assure
a stable inspection.

[0005] To deal with such an issue, several objective color unevenness
inspection techniques that are independent of the ability of an
individual inspecting staff have been proposed. Examples of such a
technique include a technique wherein the hue in a plurality of locations
within a display screen is measured using color image pickup device and
the like with an overall display screen set up in a white-color display
state to carry out a color unevenness inspection according to a magnitude
relation of values of a maximum color difference from that of white-color
display portions (Δ Euv* or Δ Eab*).

[0006] In concrete terms, for example, Japanese Unexamined Patent
Application Publication Nos. 1989-225296, 1998-2800, and 2003-57146
measure the color and brightness in several locations within a display
screen, and standardize a variation or a difference from a maximum value
and a minimum value for use in the color unevenness inspection. Further,
for example, Japanese Unexamined Patent Application Publication No.
1998-96681 pays attention to a spatial size of a color unevenness region
or a color-varying region, quantifying these for use in the color
unevenness inspection. In addition, for example, Japanese Unexamined
Patent Application Publication No. 2007-198850 proposes a technique to
evaluate a luminance unevenness for each luminance data of R (red), G
(green), and B (blue).

SUMMARY

[0007] However, in the techniques proposed in Japanese Unexamined Patent
Application Publication Nos. 1989-225296, 1998-2800, and 2003-57146, it
is possible to expect the achievement of a stable inspection by employing
an objective color unevenness inspection using standardized parameters,
although those techniques are disadvantageous in that a degree of the
color unevenness that a human perceives may vary depending on a way how
the color unevenness spreads. Further, also in the technique proposed in
Japanese Unexamined Patent Application Publication No. 1998-96681, there
is a disadvantage that a degree of the color unevenness that a human
perceives may vary depending on the hue. In addition, the technique
proposed in Japanese Unexamined Patent Application Publication No.
2007-198850 attempts to evaluate the unevenness in a case where both of
the luminance unevenness and the color unevenness occur at the same time,
although it gives no consideration on a human perception for the
luminance unevenness and the color unevenness. Therefore, this technique
does not lead to a comprehensive unevenness evaluation method in
accurately evaluating the quality of a display unit.

[0008] In other words, with existing techniques, it is difficult to carry
out a proper unevenness inspection (color unevenness inspection and
luminance unevenness inspection) due to a human visibility for the color
unevenness or the luminance unevenness, leaving room for improvement.

[0009] It is desirable to provide a unevenness inspection apparatus and a
unevenness inspection method that enable a more appropriate unevenness
inspection as compared with existing techniques.

[0010] An unevenness inspection apparatus according to an embodiment of
the present disclosure includes: an image pickup section obtaining a
pickup image of a test object; an image generating section generating
each of a color unevenness inspection image and a luminance unevenness
inspection image based on the pickup image; a calculating section
calculating an evaluation parameter using both of the color unevenness
inspection image and the luminance unevenness inspection image; and an
inspecting section performing unevenness inspection using the calculated
evaluation parameter. The calculating section calculates the evaluation
parameter in consideration of unevenness visibility for both color and
luminance.

[0011] An unevenness inspection method according to an embodiment of the
present disclosure includes: obtaining a pickup image of a test object;
generating each of a color unevenness inspection image and a luminance
unevenness inspection image based on the pickup image; calculating an
evaluation parameter using both of the color unevenness inspection image
and the luminance unevenness inspection image; and performing unevenness
inspection using the calculated evaluation parameter. The calculating the
evaluation parameter is performed in consideration of unevenness
visibility for both color and luminance.

[0012] The unevenness inspection apparatus and the unevenness inspection
method according to the embodiments of the present disclosure generate
each of the color unevenness inspection image and the luminance
unevenness inspection image based on the pickup image of the test object,
and calculate the evaluation parameter using both of the color unevenness
inspection image and the luminance unevenness inspection image,
performing unevenness inspection using the calculated evaluation
parameter. The evaluation parameter is calculated in consideration of the
unevenness visibility for both of the color and the luminance. As a
result, unlike existing techniques carrying out unevenness inspection
with disregard for such an visibility, this achieves an objective
unevenness inspection (color unevenness inspection and luminance
unevenness inspection) that is more consistent with human perception.

[0013] The unevenness inspection apparatus and the unevenness inspection
method according to the embodiments of the present disclosure calculate
the evaluation parameter using both of the color unevenness inspection
image and the luminance unevenness inspection image in consideration of
the unevenness visibility for both of the color and the luminance. As a
result, unlike existing techniques, this allows to achieve objective
unevenness inspection that is more consistent with human perception.
Consequently, it is possible to carry out more appropriate unevenness
inspection as compared with existing techniques.

[0014] It is to be understood that both the foregoing general description
and the following detailed description are exemplary, and are intended to
provide further explanation of the application as claimed.

[0015] Additional features and advantages are described herein, and will
be apparent from the following Detailed Description and the figures.

BRIEF DESCRIPTION OF THE FIGURES

[0016] The accompanying drawings are included to provide a further
understanding of the present disclosure, and are incorporated in and
constitute a part of this specification. The drawings illustrate
embodiments and, together with the specification, serve to explain the
principles of the present application.

[0017]FIG. 1 is a diagram showing a simplified configuration of a
unevenness inspection apparatus according to an embodiment of the present
disclosure with a display unit targeted for inspection.

[0018] FIG. 2 is a flow chart showing an example of a unevenness
inspection process to be performed by an image processing unit
illustrated in FIG. 1.

[0019]FIG. 3 is a characteristic diagram showing an example of a
calculation method for chroma listed in FIG. 2.

[0020] FIGS. 4A and 4B are characteristic diagrams showing examples of
relationships between an area ratio of a color unevenness region for each
color group and maximum chroma in a color unevenness region, and
subjective evaluation values for the color unevenness, respectively.

[0021] FIGS. 5A, 5B, 5C, and 5D are each a diagram showing an example of
images to be generated for a color unevenness inspection processing.

[0022] FIGS. 6A and 6B are schematic diagrams for explaining the
definition of a chroma edge region and a luminance edge region.

[0023] FIGS. 7A, 7B, 7C, and 7D are each a diagram showing an example of
images to be generated for a luminance unevenness inspection processing.

[0024] FIGS. 8A, 8B, and 8C are characteristic diagrams showing a
relationship between various subjective evaluation values and various
unevenness evaluation values according to Example 1.

[0025] FIGS. 9A and 9B are diagrams for explaining evaluation conditions
according to Example 2.

[0027] FIG. 11 is a diagram for explaining an effect in a case where the
amount of change per unit viewing angle is used as an edge threshold
value.

[0028] FIGS. 7A, 7B, and 7C are characteristic diagrams showing examples
of relationships between various subjective evaluation values and various
unevenness evaluation values.

DETAILED DESCRIPTION

[0029] Hereinafter, the embodiments of the present disclosure are
described in details with reference to the drawings. It is to be noted
that the descriptions are provided in the order given below.

1. Embodiments of the present disclosure (an example where a unevenness
inspection is carried out in consideration of the unevenness visibility
for both of the color and the luminance) 2. Modification example

Embodiments of the Present Disclosure

Configuration of Unevenness Inspection Apparatus

[0030]FIG. 1 shows a simplified configuration of a unevenness inspection
apparatus according to an embodiment of the present disclosure
(unevenness inspection apparatus 1) together with a display unit 4
targeted for inspection. The unevenness inspection apparatus 1, which is
intended to carry out a comprehensive unevenness inspection including a
color unevenness inspection and a luminance unevenness inspection for
color images displayed on the display unit 4 and the like, has an image
processing unit 2 and an image pickup unit 3 (image pickup section). As
the display unit 4, a wide variety of displays such as CRT, LCD, PDP
(Plasma Display Panel), and organic EL (Electro Luminescence) display may
be applicable. It is to be noted that a unevenness inspection method
according to an embodiment of the present disclosure is also described
hereinafter together with this embodiment because it is embodied with the
unevenness inspection apparatus 1 according to this embodiment of the
present disclosure.

(Image Pickup Unit 3)

[0031] The image pickup unit 3 is intended to take an image on a display
screen (color display screen) of the display unit 4 that is targeted for
the above-described unevenness inspection. The image pickup unit 3 is
configured using image pickup devices including, for example, CCD (Charge
Coupled Devices), CMOS (Complementary Metal Oxide Semiconductor), and
other elements. A pickup image (image pickup data Din) obtained through
image pickup by the image pickup unit 3 is output to the image processing
unit 2 via a connection wiring 10. It is to be noted that FIG. 1 shows a
case where a wired connection is used for the connection wiring 10,
although interconnection may be also made wirelessly between the image
pickup unit 3 and the image processing unit 2.

(Image Processing Unit 2)

[0032] The image processing unit 2 performs a unevenness inspection based
on the image pickup data Din being output from the image pickup unit 3,
and outputs inspection result data Dout as its inspection result, being
configured using a PC (Personal Computer) or the like as shown in FIG. 1.
The image processing unit 2 has an image generating section 21, a
parameter calculating section 22 (calculating section), and an inspection
processing section 23 (inspecting section).

[0034] The parameter calculating section 22 calculates various evaluation
parameters for unevenness inspection to be hereinafter described by using
both the color unevenness inspection image (various image data D11 to D13
described above) and the luminance unevenness inspection image (various
image data D21 to D23 described above) that are generated by the image
generating section 21. In particular, a color unevenness evaluation value
Ec (color unevenness parameter) to be hereinafter described is calculated
with the use of the color unevenness inspection images (various image
data D11 to D13). Further, a luminance unevenness evaluation value El
(luminance unevenness parameter) to be hereinafter described is
calculated with the use of the luminance unevenness inspection images
(various image data D21 to D23). Subsequently, by performing weighting
addition of the color unevenness evaluation value Ec and the luminance
unevenness evaluation value El, a total evaluation value E (total
evaluation parameter) as the above-described evaluation parameter is
calculated. At this time, according to this embodiment of the present
disclosure, the parameter calculating section 22 calculates the total
evaluation value E in consideration of the unevenness visibility for both
of the color and the luminance. It is to be noted that detailed
description on calculation processing at the parameter calculating
section 22 is also hereinafter provided.

[0035] The inspection processing section 23 uses the total evaluation
value E calculated at the parameter calculating section 22 to perform
unevenness inspection (comprehensive unevenness inspection including the
color unevenness inspection and the luminance unevenness inspection) for
the display screen of the display unit 4 that is targeted for the
unevenness inspection. With such an arrangement, the inspection result
data Dout as its inspection result is output from the inspection
processing section 23. It is to be noted that detailed description on
unevenness inspection processing at the inspection processing section 23
is also hereinafter provided.

[Operation and Effects of Unevenness Inspection Apparatus]

[0036] Subsequently, description is provided on the operation and effects
of the unevenness inspection apparatus 1 according to this embodiment of
the present disclosure.

(1. Basic Operation)

[0037] In this unevenness inspection apparatus 1, when the image pickup
unit 3 takes an image on a display screen of the display unit 4 that is
targeted for inspection, a pickup image (image pickup data Din) is
obtained. This image pickup data Din is input into the image generating
section 21 within the image processing unit 2 via the connection wiring
10.

[0038] The image generating section 21 generates each of the color
unevenness inspection images (various image data D11 to D13) and the
luminance unevenness inspection images (various image data D21 to D23) by
performing a predetermined image processing operation based on the image
pickup data Din. Subsequently, the parameter calculating section 22
calculates the total evaluation value E that is an evaluation parameter
for the unevenness inspection using both the color unevenness inspection
images and the luminance unevenness inspection images. Thereafter, the
inspection processing section 23 uses the total evaluation value E to
perform a unevenness inspection for the display screen of the display
unit 4 that is targeted for inspection. With such an arrangement, the
inspection result data Dout as its inspection result is output from the
inspection processing section 23.

(2. Details of Unevenness Inspection Process)

[0039] Next, detailed description is provided on a unevenness inspection
process by the image processing unit 2 that represents one of the
characteristic portions in the unevenness inspection apparatus 1
according to this embodiment of the present disclosure. FIG. 2 shows an
example of a unevenness inspection process to be performed by the image
processing unit 2 as a flow chart.

[0041] Next, the image generating section 21 converts a signal of the
image pickup data Din into a (Xi, Yi, Zi) signal including tristimulus
values X, Y, and Z (step S102). In concrete terms, for example, if the
image pickup data Din is an image signal conforming to the sRGB
specifications, a conversion is performed using Expression (1) given
below. Further, also for the image signal conforming to any other
specifications, the (Xi, Yi, Zi) signal is generated by performing a
conversion in accordance with the specifications in a similar manner. It
is to be noted that description is here provided on a case where a signal
of the image pickup data Din is converted into the (Xi, Yi, Zi) signal,
although the (Xi, Yi, Zi) signal may be obtained directly by the image
pickup unit 3 alternatively.

[0042] When the Din is an image signal conforming to the sRGB
specifications (in accordance with IEC 61966-2-1):

[0043] Subsequently, the image generating section 21 performs a
predetermined noise removing process as a preprocessing for the (Xi, Yi,
Zi) signal (step S103). In particular, the image generating section 21
carries out a process to remove noise caused due to types or image pickup
conditions of the image pickup unit 3 by using a spatial filter such as
Median Filter. In some cases, however, such a noise removing process may
be omitted.

[0045] In concrete terms, first, the image generating section 21
calculates (a*, b*) that is a value in the CIE 1976 L*a*b* color space
(CIELAB color space) recommended in 1976 by CIE (International Commission
on Illumination) on the basis of the (Xi, Yi, Zi) signal after being
subject to the above-described noise removing process (step S111). It is
to be noted that the CIELAB color space is recommended as a uniform color
space, representing a space in consideration of the uniformity for a
human perception of the color visibility. Here, in particular, the image
generating section 21 calculates (a*, b*) for each image pickup pixel
(display pixel) by using Expression (2) and Expression (3) given below.
It is to be noted that Xn, Yn, and Zn in these expressions are
tristimulus values on a complete diffuse reflection plane.

[0046] Thereafter, the image generating section 21 generates various color
unevenness inspection images described above while performing a
correction processing (gain correction processing) in consideration of a
difference in the color unevenness visibility depending on colors. More
specifically, the image generating section 21 calculates a chroma C while
performing such a correction processing in each image pickup pixel. In
concrete terms, first, the image generating section 21 performs a gain
correction processing (correction processing using a gain α)
expressed by Expression (4) given below as a correction processing in
consideration of a difference in the color unevenness visibility for a*
calculated in the step S111 (step S112). Subsequently, the image
generating section 21 calculates the chroma C for each image pickup pixel
with Expression (5) given below using (a*', b*) calculated in the steps
S111 and S112 (step S113).

[0047] Given a (a*, b*) coordinate system as shown in FIG. 3 for example,
such a gain correction processing corresponds to conversion (correction)
from a point of (a*, b*)=(a1, b1) into a point of (a*,
b*)=(α×a1, b1). This results in a curve indicating the chroma
C before and after the gain correction processing being just like as
shown in FIG. 3. That is, a curve indicating the chroma C before the gain
correction processing takes a circular form, whereas a curve indicating
the chroma C after the gain correction processing takes an elliptical
form instead of a circular form as shown with arrow marks in the figure
in a region of a*>0.

[0048] It is due to the following reason that the chroma C is calculated
after such a gain correction processing is completed. This is because the
color unevenness visibility that a human perceives (color unevenness
visibility) may vary depending on kinds of colors composing the color
unevenness.

[0049] In concrete terms, first, a difference in the color unevenness
visibility (ME value; subjective evaluation value of a unevenness (color
unevenness in this case) provided by a human) occurs depending on an area
ratio of the color unevenness region for each color group (area ratio of
a color unevenness region for each color group to a whole region targeted
for inspection (whole display pixel region within the display screen)).
In other words, as shown in FIG. 4A, for example, for each area ratio for
color groups corresponding to red (R)-based, orange (O)-based, and
magenta (M)-based colors, ME values (color unevenness visibility) at the
same area ratio value become higher as compared with each area ratio for
color groups corresponding to yellowish green (YG)-based, green
(G)-based, and light blue (LB)-based colors.

[0050] Further, a difference in the color unevenness visibility (ME value)
occurs also depending on a color group to which a color exhibiting a
maximum chroma Cmax (maximum chroma over a whole area of a color
unevenness region) belongs. In other words, as shown in FIG. 4B, for
example, when a color belonging to a color group corresponding to red
(R)-based, orange (O)-based, and magenta (M)-based colors exhibits the
maximum chroma Cmax, the ME value (color unevenness visibility) at the
same maximum chroma Cmax value becomes higher as compared with a case
where a color belonging to a color group corresponding to yellowish green
(YG)-based, green (G)-based, and light blue (LB)-based colors exhibits
the maximum chroma Cmax.

[0051] Therefore, according to this embodiment of the present disclosure,
the image generating section 21 calculates the chroma C while performing
a gain correction processing in consideration of a difference in the
color unevenness visibility depending on colors. In concrete terms, for a
region of a*>0 corresponding to color groups with the relatively
higher color unevenness visibility (color groups corresponding to the red
(R)-based, orange (O)-based, and magenta (M)-based colors), correction
(gain correction) to selectively increase a value of a* is performed. As
a result, unlike existing techniques carrying out unevenness inspection
(color unevenness inspection) with disregard for a difference in the
color unevenness visibility depending on colors, this achieves objective
unevenness inspection that is more consistent with human perception.

[0052] Next, the image generating section 21 uses the chroma C calculated
in the above-described manner to generate the color unevenness image
(color unevenness image data D11) that is one of the color unevenness
inspection images from the pickup image (step S114). That is, the image
generating section 21 generates a color unevenness image composed of
values of the chroma C for respective image pickup pixels. This generates
the color unevenness image composed of the color unevenness image data
D11 as shown in FIG. 5A, for example.

[0053] Subsequently, the image generating section 21 uses the calculated
chroma C again to generate the chroma edge image (chroma edge image data
D12) that is one of the color unevenness inspection images from the
pickup image (step S115). In particular, a chroma edge region is
identified by performing, for example, Sobel filtering and the like,
thereby generating the chroma edge image. More specifically, a region
exceeding a threshold (for example, (dC*/mm)=2.0) that is defined per a
unit length on a display screen to be consistent with the color
unevenness visibility perceived by a human is identified as the chroma
edge region. This results in generation of the chroma edge image composed
of the chroma edge image data D12 as shown in FIG. 5B, for example.

[0054] Here, the chroma edge region to be identified at this time is
defined as, for example, a region where the amount of change in chroma
(chroma edge intensity) per unit length in the test object (display
screen) or the amount of change in chroma per unit viewing angle is equal
to or larger than a predetermined threshold value (chroma edge threshold
value). Specifically, for example, as shown in FIG. 6A, a region (for
example, a region Ae in FIG. 6A) where the amount of change in chroma per
unit length is equal to or larger than the chroma edge threshold value
(for example, (dC*/mm)=2.0) determined per unit length on the display
screen 40 to reflect the human visibility of color unevenness may be
identified as the chroma edge region. Alternatively, for example, as
shown in FIG. 6B, a region (for example, an region Ae in FIG. 6B) where
the amount of change in chroma per unit viewing angle is equal to or
larger than the predetermined threshold value (for example, (dC*/arc
min)=0.873) determined per unit viewing angle θ of a viewer (an eye
Ey) to reflect the human visibility of color unevenness may be identified
as the chroma edge region. Here, it is desirable to use the viewing angle
θ defined as follows, for example. That is, when the eyesight of a
person is 1.0, resolution in angle recognizable by the person is
determined as 1 minute which is 1/60 of 1 degree. Therefore, considering
such human visual perception properties, the viewing angle θ is
desirably defined in minutes. This is applicable through the description
below. However, the definition of the viewing angle θ is not
limited to this definition.

[0055] Thereafter, the image generating section 21 uses the generated
color unevenness image (color unevenness image data D11) to further
generate a binary color unevenness image (binary color unevenness image
data D13), identifying a color unevenness region (step S116). At this
time, a color unevenness region is identified based on a magnitude of the
chroma C in each image pickup pixel. In concrete terms, the image pickup
pixel whose value of the chroma C exceeds the predetermined threshold
(for example, 2.0) is determined as the image pickup pixel belonging to
the color unevenness region, whereas the image pickup pixel whose value
of the chroma C is less than the predetermined threshold is determined as
the image pickup pixel not belonging to the color unevenness region,
thereby identifying the color unevenness region. This results in
identification of the color unevenness region like the binary color
unevenness image (binary color unevenness image data D13) as shown in
FIG. 5C, for example. It is to be noted that, on the binary color
unevenness image shown in FIG. 5C, a color unevenness region is displayed
in red, and any other regions are displayed in black (representing a
binary image).

[0057] In particular, the parameter calculating section 22 uses the chroma
edge image (chroma edge image data D12) to calculate a chroma edge area
ratio Sce that is an area ratio of a chroma edge region to a whole region
targeted for inspection (whole display pixel region within the display
screen).

[0058] Further, the parameter calculating section 22 uses the binary color
unevenness image (binary color unevenness image data D13) to calculate a
color unevenness area ratio Sc that is an area ratio of the color
unevenness region to the whole region targeted for inspection (whole
display pixel region within the display screen).

[0059] In addition, the parameter calculating section 22 uses the color
unevenness image (color unevenness image data D11) to calculate the
maximum chroma Cmax over the whole area of the color unevenness region.
In an example of the color unevenness image shown in FIG. 5A, the maximum
chroma Cmax is shown in the image pickup pixel indicated with a "X" mark
in FIG. 5D.

[0061] Further, the image generating section 21 and the parameter
calculating section 22 calculate the luminance unevenness evaluation
value El in the manner to be hereinafter described (steps S121 to S127).

[0062] In concrete terms, first, the image generating section 21
calculates L* (luminosity) that is a value in the above-described CIE
1976 L*a*b* color space (CIELAB color space) on the basis of the (Xi, Yi,
Zi) signal after being subject to the above-described noise removing
process (step S121). In particular, the image generating section 21
calculates L* for each image pickup pixel by using Expression (7) given
below.

L*=116(Yi/Yn)1/3-16 (7)

[0063] Thereafter, the image generating section 21 calculates average
luminance L*ave that is an average value of L* in a whole region of a
white-color image (whole display pixel region of the white-color image
displayed on the display screen of the display unit 4 in this case) (step
S122).

[0064] Next, the image generating section 21 uses L* and the average
luminance L*ave that are calculated in the above-described manner to
generate the luminance unevenness image (luminance unevenness image data
D21) that is one of the luminance unevenness inspection images from the
pickup images (step S123). In concrete terms, the image generating
section 21 calculates, for each image pickup pixel, a luminance
difference Δ L*(=L*-L*ave) that is a difference value obtained by
subtracting the average luminance L*ave from L* in each image pickup
pixel, thereby generating the luminance unevenness image composed of the
resulting luminance difference Δ L*. This generates the luminance
unevenness image composed of the luminance unevenness image data D21 as
shown in FIG. 7A, for example. It is to be noted that, at this time, the
luminance unevenness image may be generated using the value of L* instead
of generating the luminance unevenness image using the luminance
difference Δ L* as described above.

[0065] Subsequently, the image generating section 21 uses the calculated
value of L* again to generate the luminance edge image (luminance edge
image data D22) that is one of the luminance unevenness inspection images
from the pickup image (step S124). In particular, a luminance edge region
is identified by performing, for example, Sobel filtering and the like,
thereby generating the luminance edge image. More specifically, a region
exceeding a threshold (for example, (dL*/mm)=0.5) that is defined per a
unit length on the display screen to be consistent with the color
unevenness visibility perceived by a human is identified as the luminance
edge region. This results in generation of the luminance edge image
composed of the luminance edge image data D22 as shown in FIG. 7B, for
example.

[0066] Here, the luminance edge region to be identified at this time is
defined as, for example, a region where the amount of change in luminance
(luminance edge intensity) per unit length in the test object (display
screen) or the amount of change in luminance per unit viewing angle is
equal to or larger than a predetermined threshold value (luminance edge
threshold value). Specifically, for example, as shown in FIG. 6A, a
region (for example, the region Ae in FIG. 6A) where the amount of change
in luminance per unit length is equal to or larger than the luminance
edge threshold value (for example, (dL*/mm)=0.5) determined per unit
length on the display screen 40 may be identified as the luminance edge
region. Alternatively, for example, as shown in FIG. 6B, a region (for
example, the region Ae in FIG. 6B) where the amount of change in
luminance per unit viewing angle is equal to or larger than the
predetermined threshold value (for example, (dL*/arc min)=0.218)
determined per unit viewing angle θ of a viewer (an eye Ey) may be
identified as the luminance edge region.

[0067] Thereafter, the image generating section 21 uses the generated
luminance unevenness image (luminance unevenness image data D21) to
further generate the binary luminance unevenness image (binary luminance
unevenness image data D23), identifying a luminance unevenness region
(light and dark region) (step S125). At this time, the luminance
unevenness region is identified based on a magnitude of the luminance
difference Δ L* in each image pickup pixel. In concrete terms, the
image pickup pixel whose value of the luminance difference Δ L*
exceeds a predetermined threshold (for example, 0.3) is determined as the
image pickup pixel belonging to the luminance unevenness region, whereas
the image pickup pixel whose value of the luminance difference Δ L*
is less than the predetermined threshold is determined as the image
pickup pixel not belonging to the luminance unevenness region, thereby
identifying the luminance unevenness region. This results in
identification of the luminance unevenness region being identified like
the binary luminance unevenness image (binary luminance unevenness image
data D23) as shown in FIG. 7c, for example. It is to be noted that on the
binary luminance unevenness image shown in FIG. 7c, the luminance
unevenness region is displayed in white, and any other region is
displayed in black (representing a binary image).

[0069] In particular, the parameter calculating section 22 uses the
luminance edge image (luminance edge image data D22) to calculate a
luminance edge area ratio Sle that is an area ratio of the luminance edge
region to the whole region targeted for inspection (whole display pixel
region within the display screen).

[0070] Further, the parameter calculating section 22 uses the binary
luminance unevenness image (binary luminance unevenness image data D23)
to calculate a luminance unevenness area ratio Sl that is an area ratio
of the luminance unevenness region to the whole region targeted for
inspection (whole display pixel region within the display screen).

[0071] In addition, the parameter calculating section 22 uses the
luminance unevenness image (luminance unevenness image data D21) to
calculate the maximum luminance difference Δ L*max (=L*max-L*ave)
that is a difference value obtained by subtracting the average luminance
L*ave from the maximum luminance (maximum value of L*: L*max) over the
whole area of the luminance unevenness region. In an example of the
luminance unevenness image shown in FIG. 7A, the maximum luminance
difference Δ L*max is shown in the image pickup pixel indicated
with a "X" mark in FIG. 7D.

[0073] Thereafter, the parameter calculating section 22 calculates the
total evaluation value E for the unevenness inspection by using, for
example, Expression (9) given below on the basis of the color unevenness
evaluation value Ec and the luminance unevenness evaluation value El that
are obtained in the above-described manner (step S131). That is, the
parameter calculating section 22 calculates the total evaluation value E
by performing weighting addition of the color unevenness evaluation value
Ec and the luminance unevenness evaluation value El. This makes it
possible to carry out inspection that reflects the weighting of the color
unevenness evaluation value Ec and the luminance unevenness evaluation
value El in unevenness inspection to be hereinafter described. It is to
be noted that, in Expression (9), constants (coefficients) A and B denote
weighting coefficients respectively, and c3 denotes a predefined constant
(including 0).

E=A×Ec+B×El+c3 (9)

[0074] Here, according to this embodiment of the present disclosure, the
parameter calculating section 22 calculates the total evaluation value E
in consideration of the unevenness visibility for both of the color and
the luminance. In concrete terms, each of the above-described weighting
coefficients A and B is determined in consideration of the unevenness
visibility for both of the color and the luminance. In such a manner, a
calculation is made in consideration of the unevenness visibility for
both of the color and the luminance in calculating the total evaluation
value E, thereby making it possible to achieve objective unevenness
inspection that is more consistent with human perception as compared with
existing techniques carrying out unevenness inspection with disregard for
such an visibility.

[0075] Afterward, the inspection processing section 23 uses the total
evaluation value E obtained in the above-described manner to perform
unevenness inspection for the display screen of the display unit 4 that
is targeted for inspection, generating the inspection result data Dout as
its inspection result (step S132). In particular, for example, it is
determined that a degree of the unevenness (one or both of the color
unevenness and the luminance unevenness) in a test object becomes greater
as the total evaluation value E increases. On the other hand, it is
determined that the degree of the unevenness in the test object becomes
smaller as the total evaluation value E decreases. Or, the test object is
determined to be a defective product when the total evaluation value E is
equal to or larger than a predefined threshold, while the test object is
determined to be a nondefective product when the total evaluation value E
is less than the predefined threshold. Such a step completes a unevenness
inspection processing to be performed by the image processing unit 2.

Example 1

[0076] FIGS. 8A, 8B, and 8C illustrate an Example (Example 1) showing
relations (correlations) between various evaluation values described
hitherto and subjective evaluation values (ME values) evaluated by a
human. In concrete terms, FIG. 8A illustrates a correlation between the
color unevenness evaluation value Ec and the subjective evaluation value
(ME value) according to Example 1, and FIG. 8B illustrates a correlation
between the luminance unevenness evaluation value El and the subjective
evaluation value (ME value) according to Example 1, while FIG. 8c
illustrates a correlation between the total unevenness evaluation value E
and the subjective evaluation value (ME value) according to Example 1. It
is to be noted that a determination coefficient R2 in a linear line
that is shown in these figures denotes that the unevenness inspection
accuracy is enhanced as a value of R2 becomes a greater value closer
to "1".

[0077] First, an example illustrated in FIG. 8A is based on an evaluation
result by the use of a magnitude estimation method for twenty-five
persons of men and women in the age range from nineteen to twentyfour as
test subjects for the subjective evaluation. Further, in this example,
the color unevenness evaluation value Ec is calculated with the weighting
coefficient k1 of 12.8 for the chroma edge area ratio Sce, the weighting
coefficient k2 of 4.0 for the color unevenness area ratio Sc, and the
weighting coefficient k3 of 0.02 for the maximum chroma Cmax. In this
example, it is found that the determination coefficient R2 is equal
to 0.94, which indicates a quite high correlation.

[0078] Meanwhile, an example illustrated in FIG. 8B is based on an
evaluation result by the use of the magnitude estimation method under a
similar condition to the case of FIG. 8A. Further, in this example, the
luminance unevenness evaluation value El is calculated with the weighting
coefficient k4 of 19.9 for the luminance edge area ratio Sle, the
weighting coefficient k5 of 1.9 for the luminance unevenness area ratio
Sl, and the weighting coefficient k6 of 0.19 for the maximum luminance
difference Δ L*max. In this example, it is also found that the
determination coefficient R2 is equal to 0.94, which indicates a
quite high correlation.

[0079] On the other hand, an example illustrated in FIG. 8c is also based
on an evaluation result by the use of the magnitude estimation method
under a similar condition to the case of FIG. 8A. Further, in this
example, the total evaluation value E is calculated with the weighting
coefficient A of 0.63 for the color unevenness evaluation value Ec and
the weighting coefficient B of 0.71 for the luminance unevenness
evaluation value El. In this example, it is also found that the
determination coefficient R2 is equal to 0.95, which indicates a
quite high correlation.

Example 2

[0080] FIGS. 9A, 9B, and 10 illustrate an Example (Example 2) showing the
difference between edge regions when an edge region (luminance edge
region) is identified by comparing the above-described amount of change
per unit length or amount of change per unit viewing angle with the
predetermined edge threshold value.

[0081] Specifically, FIG. 9A shows the relation between the size [inch] of
the display screen targeted for inspection, and appropriate viewing
distance [mm] for a viewer and a viewing angle [°] per 1 mm for
each size (8, 40, 80 inches). FIG. 9B schematically illustrates the
relation between each of the appropriate viewing distances and the
viewing angle per 1 mm shown in FIG. 9A.

[0082] On the other hand, FIG. 10 compares, for each of the appropriate
viewing distances (each of the display screen sizes) shown in FIGS. 9A
and 9B, the luminance edge image (luminance edge image data D22) in the
case where (dL*/mm)=0.5 described above is used as the luminance edge
threshold value and the luminance edge image in the case where (dL*/arc
min)=0.218 described above is used. Namely, FIG. 10 illustrates, by
comparison, the difference in the identified edge region between the case
where the amount of change in luminance (luminance edge intensity) per
unit length in the display screen is used to define the luminance edge
region and the case where the amount of change in luminance per unit
viewing angle is used to define the luminance edge region.

[0083] According to Example 2 shown in FIGS. 9A, 9B, and 10, in the case
where the amount of change in luminance per unit viewing angle is used to
define the luminance edge region (the case of luminance edge threshold
value: (dL*/arc min)=0.218), it seems that the following effect is also
obtained. That is, the luminance edge region is allowed to be invariably
identified independent of the display screen size (appropriate viewing
distance for the viewer), unlike the case where the amount of change in
luminance per unit length in the display screen (the case of luminance
edge threshold value: (dL*/mm)=0.5) is used to define the luminance edge
region. Accordingly, the accuracy of the unevenness inspection is allowed
to be improved.

[0084] In Example 2, the description has been given of the difference
between the edge regions in identifying the luminance edge region.
However, this is similarly applicable to the difference between the edge
regions in identifying the chroma edge region. That is, in the case where
the amount of change in chroma per unit viewing angle is used to define
the chroma edge region, the chroma edge region is allowed to be
invariably identified independent of the display screen size (appropriate
viewing distance for the viewer), unlike the case where the amount of
change in chroma per unit length in the display screen is used to define
the luminance edge region.

[0085] As described above, according to this embodiment of the present
disclosure, in calculating the total evaluation value E using both of the
color unevenness inspection images (various image data D11 to D13) and
the luminance unevenness inspection images (various image data D21 to
D23), calculation is made in consideration of the unevenness visibility
for both of the color and the luminance. As a result, unlike existing
techniques, this allows to achieve objective unevenness inspection
(comprehensive unevenness inspection including the color unevenness
inspection and the luminance unevenness inspection) that is more
consistent with human perception. Consequently, it is possible to carry
out more appropriate unevenness inspection as compared with existing
techniques.

[0086] Further, in generating the color unevenness inspection images, the
chroma C is calculated while performing the correction processing (gain
correction processing for a*) in consideration of the difference in the
color unevenness visibility depending on colors in each image pickup
pixel of the pickup image. This makes it possible to achieve objective
unevenness inspection that is further consistent with human perception,
which allows that more appropriate unevenness inspection to be carried
out.

[0087] Moreover, because an objective unevenness inspection that is more
consistent with human perception is achieved, it is possible to improve
the efficiency of development and design activities by using such
unevenness inspection for the quality evaluation during the development
and design stages.

[0088] In addition, when the unevenness inspection according to this
embodiment of the present disclosure is adopted in inspection processes
for a mass-production of a product, it is possible to perform a stable
and rapid unevenness inspection, which allows the efficiency of the
inspection processes to be improved, and the product quality to be
stabilized.

[0089] In addition, in the embodiments, the amount of change (the amount
of change in luminance and that in chroma) per unit viewing angle is used
to define the edge region (the luminance edge region and the chroma edge
region). Therefore, even a small edge region on the display screen is
allowed to be identified as described below. Specifically, for example,
as shown in FIG. 11, in the case where the difference in luminance,
chroma, or the like between pixels separated with a pitch corresponding
to the viewing angle of, for example, 0.1 [rad] or more is used to
identify the edge region, for example, when the display screen size is as
large as 40 [inch] or 80 [inch], a small edge region is not allowed to be
identified. This is because, as shown in FIG. 11, the pitch on the
display screen corresponding to the viewing angle of 0.1 [rad] becomes as
large as several hundred [mm] In contrast, in the case where the amount
of change per unit viewing angle is used to define the edge region, for
example, when the unit viewing angle is 1 ['] as shown in FIG. 11, the
pitch on the display screen corresponding to this unit viewing angle is
kept to be less than 1 [mm] even if the display screen size is large.
Thus, even considering, for example, the case where the display screen
size is large, the case where the high-definition portable display is
seen with an appropriate viewing distance, or the like, a small edge
region is allowed to be identified, and thereby, the accuracy of the
unevenness inspection is allowed to be improved.

[0090] In the above description, the amount of change per unit viewing
angle is used to define the edge region. However, alternately, the
threshold value (edge threshold value) of the amount of change (the
amount of change in luminance and that in chroma) per unit length in the
display screen according to the viewing distance may be changed to define
the edge region. Specifically, the luminance edge threshold value and the
chroma edge threshold value may be determined using the expressions (10)
and (11) below, for example. It is to be noted that, in these
expressions, D represents the viewing distance [mm], Lth (=0.5)
represents the luminance edge threshold value per unit length when D=1500
[mm], and Cth (=2.0) represents the chroma edge threshold value per unit
length when D=1500 [mm]. Thus, also in the case where the edge threshold
value per unit length is changed according to the viewing distance to
define the edge region, a small edge region is allowed to be identified,
and thereby, the accuracy of the unevenness inspection is allowed to be
improved as the case where the amount of change per unit viewing angle is
used to define the edge region.

Luminance edge threshold value: (dL*/dx)=Lth×(1500/D) (10)

Chroma edge threshold value: (dC*/dx)=Cth×(1500/D) (11)

Modification Example

[0091] The present application is described hitherto by citing the
embodiment, although the present application is not limited to this
embodiment of the present disclosure, and different variations may be
made.

[0092] For example, in the above-described embodiment of the present
disclosure, the case where three parameters including the chroma edge
area ratio Sce, the color unevenness area ratio Sc, and the maximum
chroma Cmax are used as the color unevenness evaluation value Ec is
described, although other parameters may be used in addition to (or
instead of) these parameters. Moreover, one or more of these three
parameters may be used as the color unevenness evaluation value Ec.
However, it is preferable that at least two parameters of the chroma edge
area ratio Sce and the color unevenness area ratio Sc among these three
parameters be used especially. This is because a human tends to take
particular note of a spatial spreading in judging a degree of the color
unevenness, and thus these two parameters have a relatively greater
contribution to the color unevenness evaluation value Ec.

[0093] Further, in the above-described embodiment of the present
disclosure, the case where three parameters including the luminance edge
area ratio Sle, the luminance unevenness area ratio Sl, and the maximum
luminance difference Δ L*max are used as the luminance unevenness
evaluation value El is described, although other parameters may be used
in addition to (or instead of) these parameters. Moreover, one or more of
these three parameters may be used as the luminance unevenness evaluation
value El. However, it is preferable that at least two parameters of the
luminance edge area ratio Sle and the luminance unevenness area ratio Sl
among these three parameters be used especially. This is because a human
tends to take particular note of a spatial spreading in judging the
degree of the luminance unevenness, and thus these two parameters have a
relatively greater contribution to the luminance unevenness evaluation
value El.

[0094] Moreover, in the above-described embodiment of the present
disclosure, descriptions are provided by specifically citing the examples
of the color unevenness inspection image and the luminance unevenness
inspection image. However, the color unevenness inspection image and the
luminance unevenness inspection image are not limited to those images
cited in the above-described embodiment of the present disclosure.

[0095] In addition, in the above-described embodiment of the present
disclosure, the description is provided on the case where, in generating
the color unevenness inspection image, the chroma C is calculated while
performing the correction processing (gain correction processing) in
consideration of the difference in the color unevenness visibility
depending on colors, although such a gain correction processing may be
omitted in some instances.

[0096] Further, in the above-described embodiment of the present
disclosure, the description is provided on the case where the test object
for the unevenness inspection is the display screen of the display unit
for performing color image display, although the test object for the
present application may be an unit other than the display unit (for
example, a lighting unit (such as a backlight) capable of color light
emission) alternatively.

[0097] Additionally, in the above-described embodiment of the present
disclosure, the description is provided on the case where the image
pickup unit 3 and the image processing unit 2 are separated in the
unevenness inspection apparatus 1, although these units may be mounted
integrally within a same apparatus.

[0098] Moreover, a series of processes explained in the above-described
embodiment of the present disclosure may be performed with hardware
(circuits), or may be executed with software (programs).

[0099] It is possible to achieve at least the following configurations
from the above-described example embodiments and the modifications of the
disclosure.

[0100] (1) An unevenness inspection apparatus including:

[0101] an image pickup section obtaining a pickup image of a test object;

[0102] an image generating section generating each of a color unevenness
inspection image and a luminance unevenness inspection image based on the
pickup image;

[0103] a calculating section calculating an evaluation parameter using
both of the color unevenness inspection image and the luminance
unevenness inspection image; and

[0105] wherein the calculating section calculates the evaluation parameter
in consideration of unevenness visibility for both color and luminance.

[0106] (2) The unevenness inspection apparatus according to (1), wherein
the calculating section calculates a color unevenness evaluation
parameter using the color unevenness inspection image and calculates a
luminance unevenness evaluation parameter using the luminance unevenness
inspection image; and

[0107] the calculating section calculates a total evaluation parameter as
the evaluation parameter by performing weighting addition of the color
unevenness evaluation parameter and the luminance unevenness evaluation
parameter.

[0108] (3) The unevenness inspection apparatus according to (2), wherein,
when the color unevenness evaluation parameter is Ec, the luminance
unevenness evaluation parameter is El, and weighting coefficients are A
and B, the total evaluation parameter E is given by Expression (1) given
below, and each of the weighting coefficients A and B is determined in
consideration of the unevenness visibility.

E=A×Ec+B×El (1)

[0109] (4) The unevenness inspection apparatus according to (2) or (3),
wherein the inspecting section determines that a degree of unevenness in
the test object is greater as the total evaluation parameter increases,
and

[0110] the inspecting section determines that the degree of unevenness in
the test object is smaller as the total evaluation parameter decreases.

[0111] (5) The unevenness inspection apparatus according to any one of (1)
to (4), wherein the image generating section generates the color
unevenness inspection image while performing correction processing in
consideration of a difference in color unevenness visibility depending on
colors.

[0112] (6) The unevenness inspection apparatus according to (5), wherein
the image generating section calculates chroma while performing the
correction processing in each unit region of the pickup image, and uses
the calculated chroma to generate the color unevenness inspection image.

[0113] (7) The unevenness inspection apparatus according to (6), wherein
the image generating section calculates (a*, b*) in CIELAB color space in
each unit region of the pickup image, and

[0114] the image generating section performs, on the calculated a*, a gain
correction processing expressed by Expression (2) given below as the
correction processing, and then, calculates chroma C using Expression (3)
given below.

a*'=(α×a*)

(For a*>0: gain α>1; for a*=<0: gain α=1) (2)

C={(a*')2+(b*)2}1/2 (3)

[0115] (8) The unevenness inspection apparatus according to any one of (2)
to (7), wherein a chroma edge area ratio and a color unevenness area
ratio are used as the color unevenness evaluation parameter, the chroma
edge area ratio being an area ratio of a chroma edge region to a whole
region of the test object, the color unevenness area ratio being an area
ratio of a color unevenness region to the whole region of the test
object.

[0116] (9) The unevenness inspection apparatus according to (8), wherein
the chroma edge area ratio, the color unevenness area ratio, and maximum
chroma in the whole color unevenness region are used as the color
unevenness evaluation parameter.

[0117] (10) The unevenness inspection apparatus according to (9), wherein
the calculating section calculates each of the chroma edge area ratio,
the color unevenness area ratio, and the maximum chroma using the color
unevenness inspection image, and

[0118] the calculating section calculates the color unevenness evaluation
parameter by performing weighting addition of the chroma edge area ratio,
the color unevenness area ratio, and the maximum chroma.

[0119] (11) The unevenness inspection apparatus according to any one of
(8) to (10), wherein the chroma edge region is a region in which amount
of change in chroma per unit length in the test object or unit viewing
angle is equal to or larger than a predetermined threshold value.

[0120] (12) The unevenness inspection apparatus according to any one of
(2) to (11), wherein a luminance edge area ratio and a luminance
unevenness area ratio are used as the luminance unevenness evaluation
parameter, the luminance edge area ratio being an area ratio of a
luminance edge region to a whole region of the test object, the luminance
unevenness area ratio being an area ratio of a luminance unevenness
region to the whole region of the test object.

[0121] (13) The unevenness inspection apparatus according to (12), wherein
the luminance edge area ratio, the luminance unevenness area ratio, and a
maximum luminance difference are used as the luminance unevenness
evaluation parameter, the maximum luminance difference being a difference
value between maximum luminance in the whole luminance unevenness region
and an average luminance in a white-color image.

[0122] (14) The unevenness inspection apparatus according to (13), wherein
the calculating section calculates each of the luminance edge area ratio,
the luminance unevenness area ratio, and the maximum luminance difference
using the luminance unevenness inspection image, and

[0123] the calculating section calculates the luminance unevenness
evaluation parameter by performing weighting addition of the luminance
edge area ratio, the luminance unevenness area ratio, and the maximum
luminance difference.

[0124] (15) The unevenness inspection apparatus according to any one of
(12) to (14), wherein the luminance edge region is a region in which
amount of change in luminance per unit length in the test object or unit
viewing angle is equal to or larger than a predetermined threshold value.

[0125] (16) The unevenness inspection apparatus according to any one of
(1) to (15), wherein the test object is a display screen of a display
unit performing color image display.

[0126] (17) An unevenness inspection method including:

[0127] obtaining a pickup image of a test object;

[0128] generating each of a color unevenness inspection image and a
luminance unevenness inspection image based on the pickup image;

[0129] calculating an evaluation parameter using both of the color
unevenness inspection image and the luminance unevenness inspection
image; and

[0131] wherein the calculating the evaluation parameter is performed in
consideration of unevenness visibility for both color and luminance.

[0132] It should be understood that various changes and modifications to
the presently preferred embodiments described herein will be apparent to
those skilled in the art. Such changes and modifications can be made
without departing from the spirit and scope of the present subject matter
and without diminishing its intended advantages. It is therefore intended
that such changes and modifications be covered by the appended claims.